nm000106
FRL Handwriting: Handwriting Decoding from Surface Electromyography
EMG
NEMAR Dataset nm000106: handwriting - Handwriting movement detection from EMG
- Participants
- 100
- Size
- 45.3 GB
- Version
- v2.0.0
- Updated
- Jul 10, 2026
Discover datasets
100 results for "compound limb motor imagery" · page 9 of 10 · ranked by relevance
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- nm000172
High-gamma dataset described in Schirrmeister et al. 2017
EEG…motor_imagery - **Imagery tasks**: left_hand_finger_tapping, right_hand_finger_tapping…
- Participants
- 14
- Channels
- 128 (10-05)
- Citations
- 76
- HED
- v8.4.0
- Size
- 31.3 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- on004306
EEG Semantic Imagination and Perception Dataset
EEGThis dataset comprises electroencephalography (EEG) recordings from 13 participants performing semantic imagination and perception tasks across visual and auditory modalities. Participants were presented with stimuli from three semantically dissimilar categories (guitar, flower, penguin) in pictorial, orthographic, and auditory formats. The dataset includes raw, preprocessed, and epoched EEG data acquired using a 124-channel ANT-Neuro system, providing a resource for investigating neural correlates of semantic processing and cross-modal perception.
- Participants
- 12
- Channels
- 124 (10-05)
- Citations
- 1
- Size
- 79.1 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004389
Somatosensory evoked potentials in the human spinal cord to mixed and sensory nerve stimulation
EEGThis dataset comprises simultaneous multimodal neurophysiological recordings (EEG, electrospinography, electroneurography, and EMG) from 26 participants during resting state and various somatosensory stimulation conditions targeting mixed nerves (median and tibial) and individual digits. The dataset enables investigation of somatosensory evoked potentials and their propagation through the central and peripheral nervous system across multiple recording modalities.
- Participants
- 26
- Channels
- 39 (other)
- Citations
- 1
- Size
- 377 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on006095
Mind in Motion Older Adults Walking Over Uneven Terrain
EEGThis dataset comprises high-density, dual-layer electroencephalography (EEG), neck electromyography (EMG), inertial measurement unit (IMU) acceleration, and ground reaction force recordings collected from older adults walking over uneven terrain at varying speeds. Each participant completed multiple walking trials under different conditions as well as a seated rest trial, with digitized electrode locations provided. The dataset supports research into the neural and biomechanical mechanisms underlying balance and gait control during complex locomotion in aging populations.
- Participants
- 71
- Channels
- 120 (other)
- Citations
- 1
- Size
- 130 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on004696
HAPwave_bids
iEEG…Signatures of electrical stimulation driven network interactions in the human limbic system…
- Participants
- 8
- Citations
- 18
- Size
- 19.5 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on004447
The BMI-HDEEG dataset 3
EEG[
- Citations
- 10
- Size
- 20.7 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004446
The BMI-HDEEG dataset 2
EEG[
- Citations
- 10
- Size
- 29.2 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004388
Somatosensory evoked potentials in the human spinal cord to mixed nerve stimulation
EEGThis dataset comprises simultaneous multimodal neurophysiological recordings from 40 participants, including electroencephalography (EEG), electrospinography (ESG), electroneurography (ENG), and electromyography (EMG), acquired during resting state and peripheral nerve stimulation conditions. The study investigates somatosensory evoked potentials in the human spinal cord using separate median nerve stimulation (arm) and tibial nerve stimulation (leg) paradigms, as well as alternating mixed stimulation conditions, with concurrent electrocardiographic and respiratory monitoring. Data are organized according to the Brain Imaging Data Structure specification.
- Participants
- 40
- Channels
- 64 (10-10)
- Citations
- 2
- Size
- 683 GB
- Version
- v1.0.0
- Updated
- Jul 22, 2026
- on003801
Neural Tracking to go
EEGImported from OpenNeuro ds003801
- Participants
- 20
- Channels
- 24 (10-10)
- Size
- 1.15 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026